Russiagate, WikiLeaks, and the Political Economy of Posttruth News
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Problems of verification surrounded official claims concerning the role of WikiLeaks and Russia vis-à-vis the release of e-mails stolen from the Democratic National Convention before the U.S. federal election of 2016. In addition to the competing conspiracy theories and false stories promoted by fringe elements, major news organizations tailored their reporting to satisfy divergent truth markets. These developments fit with the emergence of a posttruth environment marked by increasingly fragmented media, irreconcilable portrayals of political developments, and widespread distrust of dominant institutions. However, consistent with the findings of past political economy research, most news reporting incorporated a steady stream of propaganda promoted by powerful political interests. Taken together, these realities should be understood as complementary, reflecting evolving institutional and market-driven media strategies aimed at controlling the nature and quality of information regularly made available to the public.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it